Abstract: An approach is described of structuring resources among a plurality of resources in a system architecture. A method pertaining to such approach may include accessing a knowledge base including attributes relevant to the plurality of resources. The attributes of the knowledge base may include concepts and logical relationships associated with the concepts. The method further may include, responsive to receiving at least one resource to be processed with respect to the plurality of resources, extracting characteristics from the at least one resource based upon the attributes of the knowledge base, and storing the extracted characteristics in a repository. The method further may include, responsive to an application request, creating a URI structure representing at least one matching resource among the plurality of resources that corresponds to the application request.

Abstract: A method for dynamically and cognitively generating and delivering web build layers for web applications is provided. The method may include receiving, by a computer, file requests associated with web applications. The method may further include, in response to receiving the file requests, identifying resource files associated with the file requests and the web applications by querying, by a computer, at least one application server for the resource files. Additionally, the method may include determining, by a computer, related resource files based on the identified resource files by tracking information and user activity associated with the identified resource files. The method may also include generating web build layers by grouping, by a computer, the determined related resource files. The method may further include delivering the generated optimized web build layers to the web applications based on the tracked information and user activity.

Abstract: A method for dynamically and cognitively generating and delivering web build layers for web applications is provided. The method may include receiving, by a computer, file requests associated with web applications. The method may further include, in response to receiving the file requests, identifying resource files associated with the file requests and the web applications by querying, by a computer, at least one application server for the resource files. Additionally, the method may include determining, by a computer, related resource files based on the identified resource files by tracking information and user activity associated with the identified resource files. The method may also include generating web build layers by grouping, by a computer, the determined related resource files. The method may further include delivering the generated optimized web build layers to the web applications based on the tracked information and user activity.

Abstract: A method for dynamically and cognitively generating and delivering web build layers for web applications is provided. The method may include receiving, by a computer, file requests associated with web applications. The method may further include, in response to receiving the file requests, identifying resource files associated with the file requests and the web applications by querying, by a computer, at least one application server for the resource files. Additionally, the method may include determining, by a computer, related resource files based on the identified resource files by tracking information and user activity associated with the identified resource files. The method may also include generating web build layers by grouping, by a computer, the determined related resource files. The method may further include delivering the generated optimized web build layers to the web applications based on the tracked information and user activity.

Abstract: A method for dynamically and cognitively generating and delivering web build layers for web applications is provided. The method may include receiving, by a computer, file requests associated with web applications. The method may further include, in response to receiving the file requests, identifying resource files associated with the file requests and the web applications by querying, by a computer, at least one application server for the resource files. Additionally, the method may include determining, by a computer, related resource files based on the identified resource files by tracking information and user activity associated with the identified resource files. The method may also include generating web build layers by grouping, by a computer, the determined related resource files. The method may further include delivering the generated optimized web build layers to the web applications based on the tracked information and user activity.

Abstract: Disclosed aspects include a temporal relational database management system initiating a set of operations. A set of columns in a transaction time temporal table is identified for change categorization. A change categorization model is constructed. The change categorization model is based on a set of changes with respect to the set of columns in the transaction time temporal table. The change categorization model uses a cluster analysis technique. Based on the change categorization model, a group of change categories for a set of rows coupled with the set of columns in the transaction time temporal table is determined. Based on the change categorization model, a first change category of the group of change categories is established in a first row of the set of rows.

Abstract: Disclosed aspects include a temporal relational database management system initiating a set of operations. A set of columns in a transaction time temporal table is identified for change categorization. A change categorization model is constructed. The change categorization model is based on a set of changes with respect to the set of columns in the transaction time temporal table. The change categorization model uses a cluster analysis technique. Based on the change categorization model, a group of change categories for a set of rows coupled with the set of columns in the transaction time temporal table is determined. Based on the change categorization model, a first change category of the group of change categories is established in a first row of the set of rows.

Abstract: An approach is described of structuring resources among a plurality of resources in a system architecture. A method pertaining to such approach may include accessing a knowledge base including attributes relevant to the plurality of resources. The attributes of the knowledge base may include concepts and logical relationships associated with the concepts. The method further may include, responsive to receiving at least one resource to be processed with respect to the plurality of resources, extracting characteristics from the at least one resource based upon the attributes of the knowledge base, and storing the extracted characteristics in a repository. The method further may include, responsive to an application request, creating a URI structure representing at least one matching resource among the plurality of resources that corresponds to the application request.

Abstract: Disclosed aspects include a temporal relational database management system initiating a set of operations. A set of columns in a transaction time temporal table is identified for change categorization. A change categorization model is constructed. The change categorization model is based on a set of changes with respect to the set of columns in the transaction time temporal table. The change categorization model uses a cluster analysis technique. Based on the change categorization model, a group of change categories for a set of rows coupled with the set of columns in the transaction time temporal table is determined. Based on the change categorization model, a first change category of the group of change categories is established in a first row of the set of rows.

Abstract: Disclosed aspects include a temporal relational database management system initiating a set of operations. A set of columns in a transaction time temporal table is identified for change categorization. A change categorization model is constructed. The change categorization model is based on a set of changes with respect to the set of columns in the transaction time temporal table. The change categorization model uses a cluster analysis technique. Based on the change categorization model, a group of change categories for a set of rows coupled with the set of columns in the transaction time temporal table is determined. Based on the change categorization model, a first change category of the group of change categories is established in a first row of the set of rows.

Abstract: A method, system and computer program product are provided for implementing automatic access control list validation using automatic categorization of unstructured text. Automatic categorization of unstructured text is performed on a plurality of documents of an access control list for determining an average term vector. Each of the documents is scored against the average term vector to identify a dissimilar document, flagged as a possible security risk. Automatic categorization of unstructured text is performed on user information of a plurality of members of a candidate access control list for determining a typical term vector. A similarity score is determined by user information and the typical term vector, members of an access control list that are dissimilar from other members of the access control list are identified.

Abstract: A method, system and computer program product are provided for implementing automatic access control list validation using automatic categorization of unstructured text. Automatic categorization of unstructured text is performed on a plurality of documents of an access control list for determining an average term vector. Each of the documents is scored against the average term vector to identify a dissimilar document, flagged as a possible security risk. Automatic categorization of unstructured text is performed on user information of a plurality of members of a candidate access control list for determining a typical term vector. A similarity score is determined by user information and the typical term vector, members of an access control list that are dissimilar from other members of the access control list are identified.